Modeling ITOETAM for Cloud Computing Challenges validation and developing in Tourism and Hospitality Higher Education Institutions | ||||
| International Journal of Tourism, Archaeology and Hospitality | ||||
| Volume 2, Issue 2, July 2022, Page 92-111 PDF (550.61 K) | ||||
| Document Type: Research Articles | ||||
| DOI: 10.21608/ijtah.2022.168411.1011 | ||||
 View on SCiNiTO | ||||
| Author | ||||
mohamed A alsaied 
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| hotel studies department, faculty of tourism and hotels, mansoura university | ||||
| Abstract | ||||
| Cloud computing is considered as one of the strongest innovations that has gained the attention of technological experts everywhere. It offers lots of benefits., but it also poses several security threats that no establishment can afford to ignore. The progressive education in creating nations is experiencing the issue of conveying dimension of the data and interchanges innovation. Based on these difficulties, the study attempts to develop and validate the Model for cloud computing challenges (CCC) in tourism and hospitality higher education institutions (THHEI) to find solutions to these challenges. In order to identify those challenges, the research aims to create and validate the model created by Juma and Tjahyanto (2019) for a unique model referred to as the proposed model for cloud computing adoption challenges (ITOETAM) to categories various difficulties and specific issues higher education institutions in tourism and hospitality face when using the educational cloud computing services. The model consists of five constructs named CCC, Internal, External factor (IEF), technological factors (TF), organizational factors (OF), and environmental factors (EF). The researchers relied on the following variables from the model as follows "CCC-THHEI, TF, EF and IEF. A total of 431 respondents are students, graduate students, staff, IT personnel and employees of Egyptian tourism and hotel education faculties and institutions. The research supports the "ITOETAM" concept. Which structural equation modelling (SEM) testing technique was used. The goodness of fit indices were good; they were as follows: x2 = 505.131 (df = 214), p 0.001, x2/df = 2.360, GFI = 0.912, Comparative Fit Index (CFI) = 0.953, Normed Fit Index (NFI) = 0.922, Root Mean Square Residual (RMR) = 0.071, Incremental Fit Index (IFI) = 0.954, Relative Fit Index We've talked about potential restrictions and lines of inquiry. | ||||
| Keywords | ||||
| Modeling ITOETAM; Cloud Computing Challenges; Higher Education Institutions | ||||
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